SNIP measures contextual citation impact by weighting citations based on the total number of citations in a subject field.
SJR is a prestige metric based on the idea that not all citations are the same. SJR uses a similar algorithm as the Google page rank; it provides a quantitative and a qualitative measure of the journal’s impact.
The Impact Factor measures the average number of citations received in a particular year by papers published in the journal during the two preceding years.
© Thomson Reuters Journal Citation Reports 2015
To calculate the five year Impact Factor, citations are counted in 2014 to the previous five years and divided by the source items published in the previous five years.
© Journal Citation Reports 2015, Published by Thomson Reuters
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Energy Economics is the premier field journal for energy economics and energy finance. Themes include, but are not limited to, the exploitation, conversion and use of energy, markets for energy commodities and derivatives, regulation and taxation, forecasting, environment and climate, international trade, development, and monetary policy. Contributions to the journal can use a range of methods, if appropriately and rigorously applied, including but not limited to experiments, surveys, econometrics, decomposition, simulation models, equilibrium models, optimization models, and analytical models.
Submitted papers must be http://www.elsevier.com/journals/energy-economics/0140-9883/guide-for-authors#5001replicable. Submitted papers are typically pre-reviewed by the editor-in-chief and the handling editor. Papers generally need two or more positive review reports to be invited for a revise-and-resubmit.
Energy Economics publishes an eclectic mix of papers using a wide variety of methods to shed light on a range of topics. Our replication policy reflects this, and is applied in spirit rather than to the letter. We encourage the submission of replication studies. Replication studies should reproduce the key results of the original study, replicate them and extend them in a substantive way, while explaining the differences.
For econometric papers, authors should provide program(s) and data set(s), plus a readme file on how to replicate each table, graph and other result. Ideally, there will be one command to reproduce the entire paper. Use of interactive software is discouraged. The readme file should identify the software and toolboxes used. If data are proprietary, the readme file should make clear how data can be obtained. For experimental and survey-based papers, authors should provide the original instructions (plus an English translation if applicable), information about subject eligibility and selection, the raw data, and any program used to analyze the data. For analytic papers, authors should provide data and programs used for the simulations (if any). Detailed derivations and proofs should be placed in an appendix. For papers using simulation, equilibrium or optimization models, authors should provide data and programs. If data or programs are proprietary, unambiguous information on the version should be provided, plus information on how data or programs can be obtained. Small models developed in-house should be provided. For large models developed in-house, a standard version should be provided together with a detailed description of the changes made for the version used in the paper at hand. Data and programs can be provided either as an appendix to the paper or as a stable link to a website. Data files should be in machine-readable format.
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